I almost didn’t make a best-of list this year, but as I clicked through the year’s post, it was hard not to. Iflast year (and maybe the year before) was the year of the gigantic graphic, this was the year of big data. Or maybe we’ve gotten better at filtering to the good stuff. (Fancy that.) In any case, data graphics continue to thrive and designers are putting more thought into what the data are about, and that’s a very good thing.
So here are my favorites from 2011, ordered by preference. The order could easily scramble depending when you ask me.
1. Data-Driven Documents
2. Immaterials: Light Painting WiFi
Who knew carrying around a stick that detects WiFi vertically could be so informative? Mix in long-exposure photography, and the invisible networks all around look tangible. I feel silly putting this project so high on the list because it is so simple, but its simplicity is also part of why I like it so much.
3. A More Perfect Union
Media artist Roger Luke DuBois used online dating data to show the uniqueness of cities in America. In place of city names are the words that people in those cities used more often in their online dating profiles than anywhere else. The result was an exhibit mostly on paper, showing what set cities apart. It’s not often that we get to see how geographic regions are unique at such a personal level.
From Bloom, Planetary is an iPad app that visualizes your iTunes music as a solar system, bringing your data into a more playful and exploratory context. The solar system is your music collection, stars are artists, and planets are songs. Planetary was a hit at launch, and it’s only a small sample of things to come I am sure.
5. Better Life Index
The OECD has a lot of data about countries, and it can be hard to make all of data accessible at once. Moritz Stefaner and Raureif, in collaboration with the OECD, did this with the Better Life Index. You’re even able to pick metrics to build an index yourself.
6. Whose Size 8 Are You Wearing?
This one from The New York Times amused me. My wife always has to try on so many jeans and once she finds a brand, she tends to stick with it for years. Now I get it. Sizes on women’s clothing makes no sense.
7. Radiation Dose Chart
With the troubles in Japan caused by mother nature, possible radiation hazards were in the news. Most accounts were anecdotal though, and a lot of numbers were thrown around. Randall Munroe of xkcd put together this chart to put it into perspective. What Munroe lacks in design tech he makes up with rigor.
8. The Deadliest Years
Similarly, after the tornado in Joplin, Missouri killed more than 100 people, The New York Times put things into perspective. An animated and interactive map showed tornados and where they touched down, starting in 1950.
9. See Something or Say Something
The way that people use web services has gotten a lot more interesting with the growth of mobile tech. People aren’t just interacting via a standing desktop anymore. Eric Fischer compared Flickr and Twitter usage in this series of maps. White indicates where people used both, blue is just Twitter, and orange is Flickr.
10. Visualizing Friendships
Facebook intern Paul Butler’s map came out in 2010 just after I made my top picks for that year. The map shows the reach of Facebook, and more interestingly, I think, where Facebook isn’t used. A number of follow-up maps came out of it. I also wrote a tutorial on how to do the same with your data.
11. Global Fire Observations
NASA mapped tens of millions of fires worldwide over the course of a decade. Fires come, and forestry goes, and then comes back again. I was surprised the animation wasn’t more popular when it came out. Probably would’ve spread a lot more with a little more production.
12. All Roads Lead to Philosophy
There was an idea floating around that if you continuously follow the first link on Wikipedia pages, you will always end up at philosophy. Jeffrey Winter put together a mashup to try out the idea, and whattaya know, everything does lead to philosophy. Well, almost everything.
13. Address is Approximate
While the short film about a lonely desk toy traveling cross-country via Google Streetview isn’t exactly a data visualization, it deserves a shout. I mean, it uses maps, so that’s enough. Just watch it.
[vimeo http://www.vimeo.com/32397612 w=624&h=351]
14. History of the World
Gareth Lloyd showed the history of the world in 100 seconds, using geotagged entries on Wikipedia. Because of that, the data has a slant towards Europe and the US, but it’s interesting to watch nevertheless.
15. Project Cascade
Sharing on the Web is often depicted as time series charts and bar graphs, and measured by number of retweets and likes. There’s more to it than that. The spread of a story is organic, a lot like how things spread in the physical world. Mark Hansen, Jer Thorp, and Jake Porway, as parts of the New York Times R&D Lab created Project Cascade to visualize how people share New York Times Stories.
Those are my picks for 2011. Your turn.
We are swimming in data. Too much to comprehend, at times. Matthias Shapiro walks us through the visualization techniques that can be used to figure out what a data set is trying to tell us. This work is licensed under a Creative Commons Attribution-Share Alike 3.0 United States License. Filming by Davis Audio Visual in Salt Lake City, Utah.
Aaron Koblin of Google Creative Lab gives a presentation on how computer science can be used to render artistic imaging. He stresses the importance of coupling data and art in order to create the most consumable product.
The Malofiej 20 awards, known as the Pulitzers of the infographics world, recognize the finest infographics published across the globe. This year, more than 1,500 print and online submissions competed for the prestigious awards.
National Geographic Magazine, which won best print map and two gold awards, and Internet Group do Brasil iG (gold) were notable achievements. However, as in previous years, the portfolio of graphics from the New York Times dominated the event, winning six gold medals (four print, two online), the best online map and both the ‘Best in Show’ awards for print and online submissions.
So what are the secrets to the New York Times’ continued success? Here are 10 key characteristics that, when brought together in a synthesised design process, helps to separate their work from the rest.
1. Clarity of context and purpose
Establishing the goal of a visualization or infographic is the first consideration in its development, before any creative process has commenced. Is it to enable interaction and personal discovery of data? Is it to convey a story or enhance a specific editorial perspective? Will it be a static, an interactive or even a video? All these key design decisions will be based on the clarity of concept at this initial stage of the process and this is one area in which the New York Times excels.
2. Respect for the reader
The overriding aim of a visualization or infographic should be to make a subject accessible. It is more about delivering clarity than it is about achieving simplicity. You are not looking to dilute a subject’s complexity, just make it more digestible through elegant representation. The immediacy of interpretation is not necessarily an important factor with all visual designs, as some subjects do require a little while to understand. That’s not a problem, so long as the effort put in by the reader is rewarded with the insight derived as a result. The New York Times trusts its readers to have the patience, maturity and the motivation to treasure the task of reading and learning from a graphic and this, in turn, enhances the quality of their design decisions.
3. Editorial rigor and integration
The New York Times graphics editors are seamlessly integrated into the editorial rhythm of the paper’s journalism cycle. Rather than graphics being viewed as an after-thought or novelty visual accompaniment to a written piece, many are elevated to become the central artefact of a story.
4. Clarity of questions
The strong journalistic culture of the graphics designers leads to exceptional clarity about the questions each visual piece is answering and the stories they are trying to portray. The consequence is that the choice of visual representation, whether it is an illustration, a set of visualization elements or a photographic composition, is effectively deployed and perfectly aligned to the questions they are answering.
5. Data research and preparation
One of the most important messages that came across from the New York Times speakers at Malofiej was the amount of preparation and research that goes into the construction of their graphics. Whether it is the long-term development of programming libraries that will ultimately serve as the basis of successive mapping projects, or their proximity and relationship with other departments to obtain access to rich and deep data resources, the rigor of their work is clear for all to see.
6. Visual restraint
Common to all New York Times’ pieces is the consistent and identifiable visual identity that has been carefully crafted over a number of years and which leads to real visual elegance. The deployment of color in particular is immediately recognizable. It is done so sparingly, used in such subtle doses just to highlight, distinguish or encode data without any sense of over decoration. While some may contest that their work is too sober, this is more a reflection of them not needing to overtly attract readers’ attention in the same way many other organizations or subjects do.
7. Layout and placement
Trying to secure prime ‘real estate’ page space across a newspaper like the New York Times would seem as difficult a challenge as it is to secure land on Manhattan itself. However, there is a constant boldness and ambition about the positions and dimensions in which graphics appear in the print edition. Whether it is full columns, double page spreads or dramatic diagonals, the Times ensures each graphic has the perfect stage to amplify the impact of the visual’s relationship with an article.
8. Diversity of techniques
While there is evidence of a successful and consistent formula being applied to the preparation, editorial approach and visual identity behind each New York Times graphic, the variety of techniques within their portfolio shows immense flexibility and versatility. Very rarely do you see the same representation repeated. Each piece is carefully constructed and deliberately designed to specifically answer the key questions or convey the important stories they are wishing to surface.
9. Technical Execution
Whether it is a 3D illustration, a bubble chart or an interactive map, the New York Times graphics team always demonstrates an outstanding technical capability.
Amanda Cox, the New York Times graphics editor, considers the annotation layer of their graphics to be “the most important thing we do.” Through the careful use of labels, introductions, explanatory text and captions, the New York Times’ designers take the responsibility to assist a reader in understanding the context of a graphic and interpretation of its key messages.
You can see many examples of the New York Times’ graphic output through the years on the following sites:
- Jonathan Corum’s portfolio
- Graham Roberts’ portfolio
- Kevin Quealy’s portfolio
- Marije Rooze’s thesis collection
- Small labs inc collection
Andy Kirk is a data visualisation consultant, designer and trainer and was a judge and speaker at Malofiej 20. Andy is currently delivering one-day ‘Introduction to Data Visualisation training courses around Europe and North America, providing delegates with an inspirational and educational route into this ever-popular subject.
Win a place on a Data Visualization training course!
Want to learn more about the secrets of effective data visualisation design? As a special offer to Visual.ly readers, Andy has offered one lucky person the chance to secure a free place on one of his forthcoming training events. You can view his current schedule here. To enter, simply submit a comment in the space below with your preferred location and a brief reason why you think this would be so beneficial for you. The contest will close on Monday, April 9th at 17:00 GMT, a random selection will take place and then the winner will be announced on Tuesday, April 10th.
Creating a great visualization is not as hard as it seems. Provided you have some interesting data and an effective tool with which to visualize it, a little bit of thoughtful design will lead to a decent result. That said, there are some mistakes that are very easy to make, but can ruin even a thoughtfully-made piece. Here are four data visualization mistakes you should avoid.
1. Serving the Presentation Without the Data
Which comes first: the presentation or the data? Oftentimes, in an effort to make a visualization more “interesting” or “cool”, designers will allow the presentation layer of a visualization to become more important than the data itself. The visualization captured below is an unfortunate casualty. A considerable amount of work went into it and there are parts that are informative, like the summary counters at the top left. However, without a scale or axis, the time series on the bottom right is meaningless and the 3D chart in the center is even more opaque. Tooltips (pop ups) would help, if they were there. Instead, this looks amazing, but does little.
2. Showing Too Much Detail
We all know the feeling of finding a dataset that is rich and easy to visualize, with numerous usable categorical and numerical fields. The temptation is to show everything at once, and allow users to drill down to the finest level of detail. Often, that actually makes a visualization superfluous because the user could simply look at the dataset itself if they wanted to see the finest level of detail. The trick, then, is to show enough detail to tell a story, but not so much that that story is convoluted and hidden. More data can be revealed as the reader progresses through the story. This visualization could have been great but there is so much detail it is hard to garner much information from it.
3. Not Explaining the Interactivity
Enabling users to use and interact with a visualization makes it more engaging and engrossing. However, without telling them how to use that interactivity you risk limiting them to the initial view. How you label the interactivity is just as important as doing it in the first place. Usually, informing the user at the top of the visualization (or the part they will see first) is good practice, as is calling out the interaction on or near the tools that utilize it. This visualization is actually very interesting, but without labeling the interactivity, it is easy to overlook the fact that you can click the words at the bottom of the screen to change the view. Even using a common design concept such as underlining the words to associate a hyperlink, would have been helpful.
4. Failing to Experiment
Often, your first idea is not the best idea. It is easy to get excited about a visualization and then stick to the first vision that came to your mind when you saw the data. However, it is always best to start a visualization with a blank slate of ideas. Then shift perspectives: try ten or twenty different configurations and types of chart before you settle on one. The best part about experimentation is that it often forces new findings out of the data. This chart is not ineffective, but it would be much better if it used bar or even area charts to display its information. It is actually difficult to compare the magnitude of the different parts of the “blob” with this type of view.
There is no perfect visualization, but if you can manage to stay away from these four mistakes, yours will have a much better chance of getting close to perfection.